Application of InVEST Water Yield Model for Assessing Forest Water Provisioning Ecosystem Service

Song, Cholho; Lee, Woo-Kyun; Choi, Hyun-Ah; Jeon, Seong Woo; Kim, Jae-Uk; Kim, Joon-Soon; Kim, Jung-Taek

doi:10.11108/kagis.2015.18.1.120

Cited by 11 publications

(5 citation statements)

References 12 publications

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“…The water yield of North Korean forests has, to date, not been analyzed using the InVEST model. However, InVEST water yield modeling in South Korea determined a forest ecosystem water yield for South Korea of 9,409,622,083 tons for 2011 [5] and 2,220,950,000 tons for 2000s [6] respectively. This represents a large difference from the result for North Korea (760,145,120 tons), and also the difference between two South Korean results due to the differences in the target year and parameter values for precipitation, evapotranspiration, total forested area, and seasonal factor (Z) which are used as representative indicators of forest water supplies in the InVEST water yield model.…”

Section: Discussionmentioning

confidence: 99%

“…In other words, it can be assumed that the lower precipitation and higher evapotranspiration of North Korea compared with South Korea, and deforestation in the former, has affected water yield in North Korea and its forests. With the Z parameter, the studies of South Korean forests [5,6] adopted differently, 1 and 16, respectively, and it also caused the difference in the water yield. Zhang et al [9] simulated various Z parameter values and compared them to the actual measurements for estimating the water yield.…”

Section: Discussionmentioning

confidence: 99%

“…No research into the water yield capacity of North Korea has been previously undertaken, but studies do exist for South Korea and its vicinity. Cho et al [4] and Song et al [5] used geographical information system (GIS) data to estimate the annual quantity of surface water in South Korean forests and Kim et al [6] presented the effects of afforestation on water supply with a spatio-temporal simulation of forest water yield from 1971-2010 using the InVEST water yield model. In China, a water yield analysis was performed in the watersheds of the Upper Ganga Basin, Liaohe River Basin, and in the vicinity of the Xitiaoxi River to compare field measurements of natural runoff with InVEST estimates [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

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Application of the InVEST Model to Quantify the Water Yield of North Korean Forests

Kim

Jung

2020

Forests

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The calculation and mapping of water yield are of significant importance to the effective planning and management of water resources in North Korea. In this study, we quantified and assessed the water retention capacity of North Korean forests using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) water yield model; six thematic maps were constructed and two coefficients were derived for use in the modeling. Data were obtained from the following sources: average annual precipitation from WorldClim; average monthly evapotranspiration from Global Potential Evapotranspiration (Global-PET); and the soil depth data from the International Soil Reference and Information Centre (ISRIC). The plant available water fraction was calculated using a bulk density formula. Land cover was classified using the Normalized Difference Snow, Water and Vegetation Indices, using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery. Data for the watershed analysis were provided by the World Wildlife Fund. The total water retention in North Korean forests was estimated to be 760,145,120 tons in the 2000s. However, previous studies from 2011 showed a much higher (by 9,409,622,083 tons) water retention capacity in South Korea. In North Korea, the largest monthly water storage volume occurred in July, followed by August, September, and June. This mirrors rainfall patterns, indicating that precipitation has a significant impact on water storage. Analysis of the annual spatial distribution of water storage by administrative district showed that Hamgyongnam-do had the highest, followed by Jagang-do and Gangwon-do Provinces.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Application of the InVEST Model to Quantify the Water Yield of North Korean Forests

Kim

Jung

2020

Forests

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“…In particular, this model was developed to provide decision makers with a trade-off of ecosystem services to compare the impacts of the changes in land cover or climate [30]. InVEST Water Yield (InVEST-WY) is one of the modules of the InVEST model to estimate water supply, demand and hydropower [31,32] and has been used in previous studies in Korea [33,34]. This study aims to identify the time series changes in forest water supply; thus, the InVEST-WY model was considered the most appropriate one as it allows the spatial-temporal change analysis.…”

Section: Invest Modelmentioning

confidence: 99%

Effect of National-Scale Afforestation on Forest Water Supply and Soil Loss in South Korea, 1971–2010

et al. 2017

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Afforestation of forests in South Korea may provide an example of the benefit of afforestation on precipitation storage and erosion control. In this study, we presented the effects of afforestation on water supply and soil loss prevention. A spatio-temporal simulation of forest water yield and soil loss was performed from 1971-2010 using InVEST water yield and SWAT models. A forest stock change map was produced by combining land cover data and National Forest Inventory data. The forest water yield increased about twice with changes in forest stock and climate from 1971-2010 and showed a spatially homogeneous water supply capacity. In the same period, the soil loss decreased more than three times, and the volatility of soil loss, in the 2010s, was smaller than before. The analysis of the change in forest stock without considering climate change showed an increase of 43% in forest water yield and a decrease of 87% in soil loss. An increase in precipitation increased the water yield, but also increased the soil loss volume. A change in forest stock led to positive changes in both. This study presents functional positive effects of the afforestation program in South Korea that can be useful in various afforestation programs in other countries.

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“…The probabilistic models generated by ARIES may be more appropriate for use when input data are scarce (Bagstad et al 2013). The deterministic models of InVEST have been widely evaluated at regional and national scales, and model predictions have been subjected to more rigorous testing (Song et al 2015;Salata et al 2017;Redhead et al 2018). …”

Section: Tools To Evaluate Potential Restoration Outcomesmentioning

confidence: 99%

Decision support tools for forest landscape restoration: Current status and future outlook

Chazdon¹,

Guariguata²

2018

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Application of InVEST Water Yield Model for Assessing Forest Water Provisioning Ecosystem Service

Cited by 11 publications

References 12 publications

Application of the InVEST Model to Quantify the Water Yield of North Korean Forests

Application of the InVEST Model to Quantify the Water Yield of North Korean Forests

Effect of National-Scale Afforestation on Forest Water Supply and Soil Loss in South Korea, 1971–2010

Decision support tools for forest landscape restoration: Current status and future outlook

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